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Rear lamp based vehicle detection and tracking for complex traffic conditions

Rear lamp based vehicle detection and tracking for complex t...

引用

IEEE International Conference on Networking, Sensing and control

作者： Ye Li Qingming Yao State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

In video surveillance system, detection and tracking of vehicles are two foundational and significant tasks. In this paper, a vehicle detection and tracking method based on rear lamp pairs is proposed. The proposed method combines color with motion information to perform vehicle detection. In order to adapt to different weather conditions like night, the rear lamps are divided into two categories: unlit lamps and lighted lamps. First, threshold segmentation are used to extract both the unlit and lighted lamp candidates in hue-saturation-value (HSV) color space and the thresholds are selected automatically by maximally stable extremal region (MSER) method. Then, all lamp candidates are tracked by using Kalman filter and lamp candidates with short-lived trajectories are removed to avoid disturbances. Next, two adjacent lamp candidates with similar speed are bound together as a region of interest (ROI), which represents a potential pair of lamps. Image cross-correlation symmetry analysis based on Gabor filter is utilized to find the ROIs with symmetrical texture and these symmetric ROIs can be regarded as pairs of lamps. The experimental results show that the proposed method can effectively deal with various illumination conditions and improve the accuracy and robustness of vehicle detection. In addition, this method can perform vehicle detection and tracking under complex traffic conditions and the Gabor filter based symmetry analysis can successfully suppress subtle difference between the left and right parts of a vehicle as well as environment noises.

关键词： Vehicles Image color analysis Vehicle detection Gabor filters Correlation Tracking Kalman filters

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A vehicle license plate recognition system based on analysis of maximally stable extremal regions

A vehicle license plate recognition system based on analysis...

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IEEE International Conference on Networking, Sensing and control

作者： Bo Li Bin Tian Qingming Yao Kunfeng Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

Vehicle License Plate Recognition (VLPR) system is a core module in Intelligent Transportation systems (ITS). In this paper, a VLPR system is proposed. Considering that license plate localization is the most important and difficult part in VLPR system, we present an effective license plate localization method based on analysis of Maximally Stable Extremal Region (MSER) features. Firstly, MSER detector is utilized to extract candidate character regions. Secondly, the exact locations of license plates are inferred according to the arrangement of characters in standard license plates. The advantage of this license plate localization method is that less assumption of environmental illumination, weather and other conditions is made. After license plate localization, we continue to recognize the license plate characters and color to complete the whole VLPR system. Finally, the proposed VLPR system is tested on our own collected dataset. The experimental results show the availability and effectiveness of our VLPR system in locating and recognizing all the explicit license plates in an image.

关键词： Licenses Image color analysis Character recognition Lighting Histograms Feature extraction Image segmentation

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When multivariate forecasting meets unsupervised feature learning - Towards a novel anomaly detection framework for decision support

When multivariate forecasting meets unsupervised feature lea...

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International Conference on Information systems, ICIS 2012

作者： Wang, Jiawei Ren, Jimmy Sj Wang, Wei Li, Xin Li, Qiudan Liao, Stephen S.Y. Department of Information Systems USTC-CityU Joint Advanced Research Centre 166 Ren'ai Road Suzhou China Department of Information Systems City University of Hong Kong 83 Tat Chee Avenue Hong Kong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781627486040

Many organizations adopt information technologies to make intelligent decisions during operations. Time-series data plays a crucial role in supporting such decision making processes. Though current studies on time-series based decision making provide reasonably well results, the anomaly detection essence underling most of the scenarios and the plenitude of unlabeled data are largely overlooked and left unexplored. We argue that by using multivariate forecasting and unsupervised feature learning, these two important research gaps could be filled. We carried out two experiments in this study to testify our approach and the results showed that decision support performance was significantly improved. We also proposed a novel framework to integrate the two methods so that our approach may be generalized to a larger problem domain. We discussed the advantages, the limitations and the future work of our study. Both practical and theoretical contributions were also discussed in the paper. © 2012 by the AIS/ICIS Administrative Office All rights reserved.

关键词： Decision support systems

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Application of fuzzy PID controlling technique in downhole power supply

Application of fuzzy PID controlling technique in downhole p...

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31st Chinese control Conference, CCC 2012

作者： Xinchao, Zhang Pengfeng, Li Hongxin, Chen Zengguang, Hou State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China CNOOC Research Institute Beijing 100025 China

ISBN: (纸本)9789881563811

This paper presents a novel downhole power supply control system using fuzzy PID control strategy. The control system is powered by a downhole turbine generator which generates AC voltage. The output of the turbine generator is processed through a full wave bridge rectifier and filter, and then input to the phase-shifted full-bridge PWM controller. A digital signal processor TMS320F2809 is used as the main control unit of the regulator control module. In order to verify the effectiveness of this system, a fuzzy proportion integration differentiation (F-PID) controller is used to control the phase-shifted full-bridge switching power supply, and the results presented that the controller can ensure the stability for power supply. © 2012 Chinese Assoc of Automati.

关键词： Fuzzy control

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Emergency traffic evacuation control based on the orthogonal experimental design method

Emergency traffic evacuation control based on the orthogonal...

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International Conference on Intelligent Transportation

作者： Yisheng Lv Fenghua Zhu Qinghai Miao Peijun Ye Songhang Chen State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing China

Evacuees' behaviors have a significant impact on evacuation efficiency. Evacuation clearance time is one of the key indicators in the evacuation planning and management. Evacuees' departure time choice, destination choice and route choice behavior based on real-time traffic information are three crucial factors used to estimate evacuation clearance time. In this paper, we use the orthogonal experimental design method to determine values of these three factors simultaneously, which can reduce evacuation clearance time significantly. Once we obtain these values, we can guide evacuees' departure time choice, destination choice and route choice behavior to approximate these values and evacuation efficiency will improve greatly. The dynamic traffic evacuation process is modeled using a rule-based multi-agent microscopic traffic simulation system called TransWorld. The simulation experiment results illustrate the effectiveness and reliability of the proposed method. The proposed methodology, computational results and discussions can be used for future emergency evacuation planning and management.

关键词： Transportation Computational modeling Real-time systems Design methodology Object oriented modeling Planning Traffic control

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Design and implementation of a wireless video sensor network

Design and implementation of a wireless video sensor network

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IEEE International Conference on Networking, Sensing and control

作者： Bin Tian Xue-Liang Zhao Qing-Ming Yao Lei Zha State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Jiangsu China Sciences Intelligent Engineering Company Limited Suzhou China

As a new research field in wireless sensor network (WSN), wireless video sensor network (WVSN) makes surveillance multifunctional and intelligent, with rich and intuitive sensing information. It attracts more and more researchers' attention. We design and implement a wireless video sensor network prototype system, using WIFI as the wireless communication solution and CMOS video camera as the front-end sensor. The wireless video node adopts ARM11 based embedded platform. As back-end processing algorithm, the node realizes moving object detection. Finally, we verify the sensor network system. WIFI network can transmit video sequences smoothly. The moving object detection algorithm performs well.

关键词： Wireless communication Wireless sensor networks IEEE 802.11 Standards Object detection Program processors CMOS integrated circuits Cameras

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Unscented Particle Filter with systematic Resampling Localization Algorithm Based on RSS for Mobile Wireless Sensor Networks

Unscented Particle Filter with Systematic Resampling Localiz...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Zhengjie Wang Xiaoguang Zhao Xu Qian School of Mechanical Electronic & Information Engineering China University of Mining & Technology (Beijing) Beijing China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467358088

We consider the problem of mobile sensor node localization and propose an unscented particle filter algorithm in wireless sensor networks (WSNs) consisting of mobile nodes and static anchor nodes. Because the received signal strength (RSS) varies obviously, we employ particle filter to decrease the bad effect. We first form the system state model, mobile model, and RSS model, and then apply unscented particle filter and utilize the systematic resample to decrease the degeneration of the particle. We eliminate the uncertain of the RSS in wireless channel and get accurate location of mobile nodes. The predicted position of the mobile node is constrained by its velocity and the measurement value of RSS. We do a lot of simulation to validate the algorithm by assigning different parameters. Simulation results show that the algorithm enhances the localization accuracy of mobile node compared with the standard particle filter algorithm.

关键词： Mobile wireless sensor networks Localization Received signal strength (RSS) Unscented particle filter systematic resampling Wireless sensor networks RSS gene Really Simple Syndication REACTOR SAFETY STUDY Particle filters Particle filtering algorithm Mobile Mobile nodes Resampling Values in measurement wireless channels

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Research on intelligent scientific research collaboration platform and taking journal intelligence system as example

Research on intelligent scientific research collaboration pl...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Lu, Hao Zheng, Xiaolong Sun, Xingkai Zhang, Nan State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan China Beijing Engineering Research Center of IntelligentSystems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Chinese Association of Automation Beijing China

ISBN: (纸本)9781467324007

Currently, the research issues are becoming increasingly global and complex. In order to master more and more professional and comprehensive ability to solve problems, it is proposed in this paper that academic intelligence, journal intelligence, conference intelligence, paper intelligence and so on are integrated together to establish intelligent scientific research collaboration platform. And taking the system application of Science and Technology Review as example, the process of scientific research collaboration is carried out to verify the effectiveness of the system. In conclusion, the scientific research collaboration platform could satisfy the comprehensive needs for effectively acquiring a mass of information and launching scientific research collaboration as well as facilitating academic communication. © 2012 IEEE.

关键词： scientific research Intelligence Platform journals

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Extracting opinion explanations from Chinese online reviews

Extracting opinion explanations from Chinese online reviews

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Yuequn Li Wenji Mao Daniel Zeng Luwen Huangfu Chunyang Liu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson Tucson AZ USA CNCERT/CC Beijing China

Opinion mining has gained increasing attention and shown great practical value in recent years. Existing research on opinion mining mainly focuses on the extraction of lexicon orientation and opinion targets. The explanations of opinions, which are potentially valuable for many applications, are totally ignored. To address this specific research challenge, in this paper, we propose an approach to extract the explanation of reason and/or consequence behind an opinion via learning word pairs and using causal indicators from Chinese online reviews. We also improve our word pair based method by constructing clusters of word paris. Experiments on a Chinese business review corpus show that our method is feasible and effective.

关键词： Feature extraction Accuracy Semantics Data mining Thesauri Cities and towns Probability

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Acquiring netizen group's opinions for modeling food safety events

Acquiring netizen group's opinions for modeling food safety ...

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Zhangwen Tan Wenji Mao Daniel Zeng Xiaochen Li Xiuguo Bao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Management Information Systems University of Arizona Tucson Tucson AZ USA CNCERT/CC Beijing China

Food safety events are typical public security events that draw great public concern. In food safety events, millions of netizens pay close attention to the event, express their opinions online and thus influence the decisions of government or food producers. Modeling netizen groups, especially the dynamics of their opinions in these events, can help us understand the mechanism and evolvement of such events and provide valuable insights for social management. However, conventional computational models, such as agent-based models, are usually constructed manually. In this paper, we propose an approach to acquiring netizen group's opinions from online comments to facilitate the modeling of food safety events. We conduct experimental study on typical events happened in China and empirically evaluate the performance of our proposed approach. The results verify the effectiveness of the approach.

关键词： Safety Internet Computational modeling Government Syntactics Feature extraction Media

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